By the end of this course, students should have learned:

1. To provide an overview of research-driven goals
2. To define a general linear model
3. To discuss data expression    
4. To build linkage between correlation and ANOVA
5. To identify problem typologies traditional to correlation/ANOVA applications
6. To extend models to non-linear contexts

1.  Principles Of Research Design
2.  Basics: Correlation	
3.  Correlation	
4.  ANOVA	
5.  Regression/Correlation	
6.  Significance And Hypothesis Testing		
7.  Coding For Experiments - MRC	
8.  Overall Analysis - ANOVA vs. MRC	
9.  MRC And Degrees Of Freedom	
10. Detailed Analyses	
11. Family-Wise Correction	
12. Factorial - Main/Simple Effects	
13. Interaction Comparisons	
14. Within Subjects	
15. Mixed Designs	
16. Polynomial Trend Analysis